Some tutorials

A good starting point is EasyVVUQ - Basic Concepts, followed by some information on encoders and decoders How to Set-up Your Simulation Code for Use With EasyVVUQ: Encoders and Decoders.

Examples based on the Ishigami function

1. Run an EasyVVUQ campaign to analyze the sensitivity for the Ishigami function using MCsampler

2. Sensitivity analysis for the Ishigama function using PCE

3. Sensityivity analysis for the Ishigama function with noise using PCE

Examples based on the fusion workflow

1. Run the fusion EasyVVUQ campaign using PCE

2. Run the fusion EasyVVUQ campaign using SC

3. EasyVVUQ fusion tutorial

Examples using QCG-PJ

1. Running EasyVVUQ on HPC resources with QCG-PilotJob

Examples using Polynomial Chaos Expansion (PCE)

1. EasyVVUQ - Basic Concepts

2. Run the fusion EasyVVUQ campaign using PCE

3. EasyVVUQ fusion tutorial

4. Sensitivity analysis for the Ishigama function using PCE

5. Sensityivity analysis for the Ishigama function with noise using PCE

6. EasyVVUQ - Jinja encoder tutorial

7. EasyVVUQ and Cloud Execution via Kubernetes

8. EasyVVUQ - Vector Quantities of Interest

9. A Cooling Coffee Cup with Polynomial Chaos Expansion

10. A Cooling Coffee Cup with Polynomial Chaos Expansion

Examples using Stochastic Collocation (SC)

1. Running EasyVVUQ on HPC resources with QCG-PilotJob

2. Dimension adaptive sampling tutorial

3. Dimension adaptive sampling tutorial applied to the fusion example

4. Run the fusion EasyVVUQ campaign using SC

5. Sensitivity analysis of Ishigami function with Stochastic Collocation

6. EasyVVUQ Tutorial

7. Simplex Stochastic Collocation tutorial

Examples using MC, QMC or MCMC Sampling

1. Run an EasyVVUQ campaign to analyze the sensitivity for the Ishigami function using MCsampler

2. Markov-Chain Monte Carlo in EasyVVUQ

3. EasyVVUQ Tutorial

Examples using Adaptive Dimension

1. Dimension adaptive sampling tutorial

2. Dimension adaptive sampling tutorial applied to the fusion example

Examples using Kubernetes

1. EasyVVUQ and Cloud Execution via Kubernetes

2. EasyVVUQ Tutorial

Table of tutorials

• Running EasyVVUQ on HPC resources with QCG-PilotJob
• EasyVVUQ - Basic Concepts
• Dimension adaptive sampling tutorial applied to the fusion example
• Dimension adaptive sampling tutorial
• Run the fusion EasyVVUQ campaign using PCE
• Run the fusion EasyVVUQ campaign using SC
• EasyVVUQ fusion tutorial
• EasyVVUQ in R
• Run an EasyVVUQ campaign to analyze the sensitivity for the Ishigami function using MCsampler
• Sensitivity analysis of Ishigami function with Stochastic Collocation
• Sensitivity analysis for the Ishigama function using PCE
• Sensityivity analysis for the Ishigama function with noise using PCE
• MCMC in EasyVVUQ
• How to Set-up Your Simulation Code for Use With EasyVVUQ: Encoders and Decoders
• Exploration of the effect of aleatoric uncertainties on Sobol Coefficients
• Tuning the hyperparameters of a neural network using EasyVVUQ and FabSim3
• Executing a grid search on a remote host
• Tuning the hyperparameters of a neural network using EasyVVUQ
• EasyVVUQ - Jinja encoder tutorial
• EasyVVUQ and Cloud Execution via Kubernetes
• Markov-Chain Monte Carlo in EasyVVUQ
• EasyVVUQ Tutorial
• Introduction
• Installing EasyVVUQ
• Epidemiological Model
• EasyVVUQ Set-up
• Parameter Sweep
• Remote Execution
• Sensitivy Analysis with QMC
• Using Stochastic Collocation
• Simplex Stochastic Collocation tutorial
• EasyVVUQ - Vector Quantities of Interest
• A Cooling Coffee Cup with Polynomial Chaos Expansion
• A Cooling Coffee Cup with Polynomial Chaos Expansion